Multivariate exponential survival trees and their application to tooth prognosis

Computational Statistics and Data Analysis

Volumn 53, Issue 4, 2009, Pages 1110-1121

  Fan, Juanjuan ^a   Nunn, Martha E ^b   Su, Xiaogang ^c  

^a SAN DIEGO STATE UNIVERSITY   (United States)

^b BOSTON UNIVERSITY   (United States)

^c UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL EFFICIENCY; LEARNING SYSTEMS; METALS;

FRAILTY MODELS; MACHINE-LEARNING; RANDOM FORESTS; RELATIVE IMPORTANCE; SIMULATION STUDIES; TREE SIZE;

DENTISTRY;

EID: 58549109024     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2008.10.019     Document Type: Article

References (20)

1. Akaike H. A new look at model identification. IEEE Transactions an Automatic Control 19 (1974) 716-723
2. Breiman L. Random forests. Machine Learning 45 (2001) 5-32
3. Breiman L., Friedman J., Olshen R., and Stone C. Classification and Regression Trees (1984), Wadsworth International Group, Belmont, CA
4. Butler, J., Gilpin, E., Gordon, L., Olshen, R., 1989. Tree-structured survival analysis, II. Technical Report. Stanford University, Department of Biostatistics
5. Ciampi A., Thiffault J., Nakache J.-P., and Asselain B. Stratification by stepwise regression, correspondence analysis and recursive partition. Computational Statistics and Data Analysis 4 (1986) 185-204
6. Clayton D.G. A model for association in bivariate life tables and its application in epidemiologic studies of familial tendency in chronic disease incidence. Biometrika 65 (1978) 141-151
7. Clayton D.G., and Cuzick J. Multivariate generalization of the proportional hazards model. Journal of the Royal Statistical Society, Series A 148 (1985) 82-108
8. Davis R., and Anderson J. Exponential survival trees. Statistics in Medicine 8 (1989) 947-962
9. Efron B. Estimating the error rate of a prediction rule: Improvements on cross-validation. Journal of American Statistical Association 78 (1983) 316-331
10. Gao F., Manatunga A.K., and Chen S. Identification of prognostic factors with multivariate survival data. Computational Statistics and Data Analysis 45 (2004) 813-824
11. Gordon L., and Olshen R. Tree-structured survival analysis. Cancer Treatment Reports 69 (1985) 1065-1069
12. LeBlanc M., and Crowley J. Relative risk trees for censored survival data. Biometrics 48 (1992) 411-425
13. LeBlanc M., and Crowley J. Survival trees by goodness of split. Journal of the American Statistical Association 88 (1993) 457-467
14. Lin D.Y. Cox regression analysis of multivariate failure time data: The marginal approach. Statistics in Medicine 13 (1994) 2233-2247
15. Marshall A.W., and Olkin I. A multivariate exponential distribution. Journal of American Statistical Association 62 (1967) 30-44
16. McGuire M.K., and Nunn M.E. Prognosis versus actual outcome. II: The effectiveness of commonly taught clinical parameters in developing an accurate prognosis. Journal of Periodontology 67 (1996) 658-665
17. McGuire M.K., and Nunn M.E. Prognosis versus actual outcome. III: The effectiveness of clinical parameters in accurately predicting tooth survival. Journal of Periodontology 67 (1996) 666-674
18. Segal M.R. Regression tress for censored data. Biometrics 44 (1988) 35-47
19. Su X.G., and Fan J.J. Multivariate survival trees: A maximum likelihood approach based on frailty models. Biometrics 60 (2004) 93-99
20. Su X.G., Fan J.J., Wang A., and Johnson M. On simulating multivariate failure times. International Journal of Applied Mathematics and Statistics 5 (2006) 8-18